Search results for: optimizing

Authors: Kesi Widjajanti

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To develop the growth of small and medium enterprises (SMEs), it is important to unlock potential resources that can improve their performance. Business Partnerships (BP) are currently an interesting topic of strategy to use to expand markets and maximize financial and marketing performance. However, many business partnerships have not quite a role among small and medium companies in the creative industry in the Batik Craft sector in Indonesia. This study is rooted in the Resource Advantage Theory of Competition ( RAToC), which emphasizes that the advantage of company resources can be sourced from organizational and relational resources. With the basis of this theory, SMEs can optimize the allocation of relational resources and organizational goals, improve operational efficiency, and gain a strategic advantage in the market. Companies that are able to actualize organizational and relational resources better than other market players can be used for the process of increasing their superior performance. This study explores key elements from the RAToC perspective and shows how Business Partnerships have the potential to drive SMEs' growth. By aligning visions, and organizational resources, sharing knowledge and leveraging complementary relational resources, SMEs can increase their competitiveness, enter new markets, and achieve superior performance. The theoretical contribution of RAToC in small companies is due to the role of Pro-Grow Business Partnership strength as an important antecedent for improving SMEs' performance. The benefits (scenarios) of a Business Partnership to grow together are directed at optimizing resources that can create additional value for customers so that they can outperform competitors. Furthermore, managerial implications for SMEs who wish to unlock their resource potential can encourage the role of Pro-Grow Business Partnerships, which have specific characteristics, can absorb experience/knowledge capacity and utilize this knowledge for the development of "together" business ventures.

Keywords: pro grow business partnership, performance, SMEs, resources advantage theory of competition, industry kreatif batik handycraft indonesia

Procedia PDF Downloads 44

Authors: Rumaisa Shahid, Saad Aziz Durrani, Shameel Pervez, Ibatsam Khokhar

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Food waste is a prevalent issue in Pakistan, with over 40 percent of food discarded annually. Despite their decay, rotting fruits retain residual nutritional value consumed by microorganisms, notably fungi and bacteria. Fungi, preferred for their extracellular enzyme release, are gaining prominence, particularly for pectinase production. This enzyme offers several advantages, including clarifying juices by breaking down pectic compounds. In this study, three Aspergillus flavus isolates derived from decomposed fruits and manure were selected for pectinase production. The primary aim was to isolate fungi from diverse waste sources, identify the isolates and assess their capacity for pectinase production. The identification was done through morphological characteristics with the help of Light microscopy and Scanning Electron Microscopy (SEM). Pectinolytic potential was screened using pectin minimal salt agar (PMSA) medium, comparing clear zone diameters among isolates. Identification relied on morphological characteristics. Optimizing substrate (lemon and orange peel powder) concentrations, pH, temperature, and incubation period aimed to enhance pectinase yield. Spectrophotometry enabled quantitative analysis. The temperature was set at room temperature (28 ºC). The optimal conditions for Aspergillus flavus strain AF1(isolated from mango) included a pH of 5, an incubation period of 120 hours, and substrate concentrations of 3.3% for orange peels and 6.6% for lemon peels. For AF2 and AF3 (both isolated from soil), the ideal pH and incubation period were the same as AF1 i.e. pH 5 and 120 hours. However, their optimized substrate concentrations varied, with AF2 showing maximum activity at 3.3% for orange peels and 6.6% for lemon peels, while AF3 exhibited its peak activity at 6.6% for orange peels and 8.3% for lemon peels. Among the isolates, AF1 demonstrated superior performance under these conditions, comparatively.

Keywords: pectinase, lemon peel, orange peel, aspergillus flavus

Procedia PDF Downloads 36

Authors: Wade Ghribi, Abdelmoty M. Ahmed, Ahmed Said Badawy, Belgacem Bouallegue

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In higher education institutions, the most pressing priority is to improve student performance and retention. Large volumes of student data are used in Educational Data Mining techniques to find new hidden information from students' learning behavior, particularly to uncover the early symptom of at-risk pupils. On the other hand, data with noise, outliers, and irrelevant information may provide incorrect conclusions. By identifying features of students' data that have the potential to improve performance prediction results, comparing and identifying the most appropriate ensemble learning technique after preprocessing the data, and optimizing the hyperparameters, this paper aims to develop a reliable students' performance prediction model for Higher Education Institutions. Data was gathered from two different systems: a student information system and an e-learning system for undergraduate students in the College of Computer Science of a Saudi Arabian State University. The cases of 4413 students were used in this article. The process includes data collection, data integration, data preprocessing (such as cleaning, normalization, and transformation), feature selection, pattern extraction, and, finally, model optimization and assessment. Random Forest, Bagging, Stacking, Majority Vote, and two types of Boosting techniques, AdaBoost and XGBoost, are ensemble learning approaches, whereas Decision Tree, Support Vector Machine, and Artificial Neural Network are supervised learning techniques. Hyperparameters for ensemble learning systems will be fine-tuned to provide enhanced performance and optimal output. The findings imply that combining features of students' behavior from e-learning and students' information systems using Majority Vote produced better outcomes than the other ensemble techniques.

Keywords: educational data mining, student performance prediction, e-learning, classification, ensemble learning, higher education

Procedia PDF Downloads 74

Authors: Himanshu Shekhar Maharana, S. K .Dash

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Economic Load Dispatch (ELD) proves to be a vital optimization process in electric power system for allocating generation amongst various units to compute the cost of generation, the cost of emission involving global warming gases like sulphur dioxide, nitrous oxide and carbon monoxide etc. In this dissertation, we emphasize ramp rate constriction factor based particle swarm optimization (RRCPSO) for analyzing various performance objectives, namely cost of generation, cost of emission, and a dual objective function involving both these objectives through the experimental simulated results. A 6-unit 30 bus IEEE test case system has been utilized for simulating the results involving improved weight factor advanced ramp rate limit constraints for optimizing total cost of generation and emission. This method increases the tendency of particles to venture into the solution space to ameliorate their convergence rates. Earlier works through dispersed PSO (DPSO) and constriction factor based PSO (CPSO) give rise to comparatively higher computational time and less good optimal solution at par with current dissertation. This paper deals with ramp rate and constriction factor based well defined ramp rate PSO to compute various objectives namely cost, emission and total objective etc. and compares the result with DPSO and weight improved PSO (WIPSO) techniques illustrating lesser computational time and better optimal solution. 

Keywords: economic load dispatch (ELD), constriction factor based particle swarm optimization (CPSO), dispersed particle swarm optimization (DPSO), weight improved particle swarm optimization (WIPSO), ramp rate and constriction factor based particle swarm optimization (RRCPSO)

Procedia PDF Downloads 351

Authors: Emrah Ayhan, Puspa Saananta Irfani, Ömer Doğukan Şahin

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Public services, which are important for the order and continuity of social life, have begun to transform into electronic services (E-service) with the development of information and communication technologies in recent years. In particular, as a result of the widespread use of the internet and the increase in citizen demands, it has become necessary to provide public services electronically. In addition to facilitating traditional public services, new types of e-services strengthen the interaction, cooperation, accessibility, transparency, citizen participation (e-governance) and accountability between citizens and the state. In this context, the factors in the literature that are considered to influence the citizens’ satisfaction towards e-services will be examined through the example of student satisfaction with the e-services (Anasis, Mergen, E-mail, library, cafeteria and other transactions) offered by Anadolu University (Eskişehir, Türkiye) through university website and mobile application. The data for the analysis will be obtained from the survey research that will be used to measure user satisfaction with university e-services of 1,000 students studying at 9 different faculties and graduate schools of Anadolu University. These data will be analyzed with a unique methodology that uses the E-GovQual model and Importance Performance Analysis (IPA) methods together. The e-GovQual model serves as a framework for evaluating the quality of e-services, allowing a detailed understanding of students' perceptions. On the other hand, the IPA method will be used to determine the performance level of Anadolu University in the provision of e-services and to understand the areas that require improvement and student expectations. Strategic goals and suggestions will be made to decision-makers, students, and researchers in line with the findings obtained in the research. Thus, it is planned to contribute to e-governance and user satisfaction in educational institutions and to reveal practical implications for optimizing online platforms to better serve student needs.

Keywords: e-service, Anadolu university, student satisfaction, e-governance, e-govqual, importance performance analysis

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Authors: Arash Rafiei, Carroll Moore

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Leaching process as the first stage of hydrometallurgy is a multidisciplinary system including material properties, chemistry, reactor design, mechanics and fluid dynamics. Therefore, doing leaching system optimization by pure scientific methods need lots of times and expenses. In this work, a mixture of two titanium ores and one titanium slag are used for extracting titanium for leaching stage of TiO2 pigment production procedure. Optimum titanium extraction can be obtained from following strategies: i) Maximizing titanium extraction without selective digestion; and ii) Optimizing selective titanium extraction by balancing between maximum titanium extraction and minimum impurity digestion. The main difference between two strategies is due to process optimization framework. For the first strategy, the most important stage of production process is concerned as the main stage and rest of stages would be adopted with respect to the main stage. The second strategy optimizes performance of more than one stage at once. The second strategy has more technical complexity compared to the first one but it brings more economical and technical advantages for the leaching system. Obviously, each strategy has its own optimum operational zone that is not as same as the other one and the best operational zone is chosen due to complexity, economical and practical aspects of the leaching system. Experimental design has been carried out by using Taguchi method. The most important advantages of this methodology are involving different technical aspects of leaching process; minimizing the number of needed experiments as well as time and expense; and concerning the role of parameter interactions due to principles of multifactor-at-time optimization. Leaching tests have been done at batch scale on lab with appropriate control on temperature. The leaching tank geometry has been concerned as an important factor to provide comparable agitation conditions. Data analysis has been done by using reactor design and mass balancing principles. Finally, optimum zone for operational parameters are determined for each leaching strategy and discussed due to their economical and practical aspects.

Keywords: titanium leaching, optimization, experimental design, performance analysis

Procedia PDF Downloads 342

Authors: Saeed M. Alshahrani

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This research integrated blockchain technology to reform medical records management in healthcare informatics. It was aimed at resolving the limitations of centralized systems by establishing a secure, decentralized, and user-centric platform. The system was architected with a sophisticated three-tiered structure, integrating advanced cryptographic methodologies, consensus algorithms, and the Fast Healthcare Interoperability Resources (HL7 FHIR) standard to ensure data security, transaction validity, and semantic interoperability. The research has profound implications for healthcare delivery, patient care, legal compliance, operational efficiency, and academic advancements in blockchain technology and healthcare IT sectors. The methodology adapted in this research comprises of Preliminary Feasibility Study, Literature Review, Design and Development, Cryptographic Algorithm Integration, Modeling the data and testing the system. The research employed a permissioned blockchain with a Practical Byzantine Fault Tolerance (PBFT) consensus algorithm and Ethereum-based smart contracts. It integrated advanced cryptographic algorithms, role-based access control, multi-factor authentication, and RESTful APIs to ensure security, regulate access, authenticate user identities, and facilitate seamless data exchange between the blockchain and legacy healthcare systems. The research contributed to the development of a secure, interoperable, and decentralized system for managing medical records, addressing the limitations of the centralized systems that were in place. Future work will delve into optimizing the system further, exploring additional blockchain use cases in healthcare, and expanding the adoption of the system globally, contributing to the evolution of global healthcare practices and policies.

Keywords: healthcare informatics, blockchain, medical records management, decentralized architecture, data security, cryptographic algorithms

Procedia PDF Downloads 34

Authors: Alexander A. Tokmakov

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Cell-free protein synthesis is widely used to synthesize recombinant proteins. It allows genome-scale expression of various polypeptides under strictly controlled uniform conditions. However, only a minor fraction of all proteins can be successfully expressed in the systems of protein synthesis that are currently used. The factors determining expression success are poorly understood. At present, the vast volume of data is accumulated in cell-free expression databases. It makes possible comprehensive bioinformatics analysis and identification of multiple features associated with successful cell-free expression. Here, we describe an approach aimed at identification of multiple physicochemical and structural properties of amino acid sequences associated with protein solubility and aggregation and highlight major correlations obtained using this approach. The developed method includes: categorical assessment of the protein expression data, calculation and prediction of multiple properties of expressed amino acid sequences, correlation of the individual properties with the expression scores, and evaluation of statistical significance of the observed correlations. Using this approach, we revealed a number of statistically significant correlations between calculated and predicted features of protein sequences and their amenability to cell-free expression. It was found that some of the features, such as protein pI, hydrophobicity, presence of signal sequences, etc., are mostly related to protein solubility, whereas the others, such as protein length, number of disulfide bonds, content of secondary structure, etc., affect mainly the expression propensity. We also demonstrated that amenability of polypeptide sequences to cell-free expression correlates with the presence of multiple sites of post-translational modifications. The correlations revealed in this study provide a plethora of important insights into protein folding and rationalization of protein production. The developed bioinformatics approach can be of practical use for predicting expression success and optimizing cell-free protein synthesis.

Keywords: bioinformatics analysis, cell-free protein synthesis, expression success, optimization, recombinant proteins

Procedia PDF Downloads 384

Authors: Amir A. Beltagi, Ahmed R. Abdelbaki

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Background: Core stability training has recently attracted attention for optimizing performance and improving muscle balance for healthy and unhealthy individuals. The purpose of this study was to investigate the effect of beginner’s core stability exercises on the trunk flexors’/extensors’ peak torque ratio and trunk flexors’ and extensors’ peak torques. Methods: Thirty five healthy individuals, randomly assigned into two groups; experimental (group I) and control (group II), participated in the study. Group I involved 20 participants (10 male & 10 female) with mean ±SD age, weight, and height of 20.7±2.4 years, 66.5±12.1 kg and 166.7±7.8 cm respectively. Group II involved 15 participants (6 male & 9 female) with mean ±SD age, weight, and height of 20.3±0.61 years, 68.57±12.2 kg and 164.28 ±7.59 cm respectively. Data were collected using the Biodex Isokinetic system. The participants were tested twice; before and after a 6-week period during which the experimental group performed a core stability training program. Findings: Statistical analysis using the 2x2 Mixed Design ANOVA revealed that there were no significant differences in the trunk flexors’/extensors’ peak torque ratio between the ‘pre’ and ‘post’ tests for either group (p > 0.025). Moreover, there were no significant differences in the trunk flexors’/extensors’ ratios between both groups at either test (p > 0.025). Meanwhile, the 2x2 Mixed Design MANOVA revealed that there were significant differences in the trunk flexors’ and extensors’ peak torques between the ‘pre’ and ‘post’ tests for group I (p < 0.025), while there were no significant differences inbetween for group II (p > 0.025). Moreover, there were no significant differences between both groups for the tested muscles’ peak torques at either test except for that of the trunk flexors at the ‘post’ test only (p < 0.025). Interpretation: The improvement in muscle performance indicated by the increase in the trunk flexors’ and extensors’ peak torques in the experimental group recommends including core stability training in the exercise programs that aim to improve muscle performance.

Keywords: core stability, isokinetic, trunk muscles, muscle balance

Procedia PDF Downloads 274

Authors: Mequanint Birhan

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Modern urban environments present a dynamically growing field where, notwithstanding shared goals, several mutually conflicting interests frequently collide. However, it has a big impact on the city's socioeconomic standing, waiting lines and queues are common occurrences. This results in extremely long lines for both vehicles and people on incongruous routes, service coagulation, customer murmuring, unhappiness, complaints, and looking for other options sometimes illegally. The root cause of this is corruption, which leads to traffic jams, stopping, and packing vehicles beyond their safe carrying capacity, and violating the human rights and freedoms of passengers. This study focused on the optimizing time of passengers had to wait in public vehicle stations. This applied research employed both data gathering sources and mixed approaches, then 166 samples of key informants of transport station were taken by using the Slovin sampling formula. The length of time vehicles, including the drivers and auxiliary drivers ‘Weyala', had to wait was also studied. To maximize the service level at vehicle stations, a queuing model was subsequently devised ‘Menaharya’. Time, cost, and quality encompass performance, scope, and suitability for the intended purposes. The minimal response time for passengers and vehicles queuing to reach their final destination at the stations of the Tepi, Mizan, and Bonga towns was determined. A new bus station system was modeled and simulated by Arena simulation software in the chosen study area. 84% improvement on cost reduced by 56.25%, time 4hr to 1.5hr, quality, safety and designed load performance calculations employed. Stakeholders are asked to put the model into practice and monitor the results obtained.

Keywords: Arena 14 automatic rockwell, queue, transport services, vehicle stations

Procedia PDF Downloads 49

Authors: Atom Mkhitaryan, Astghik Avetisyan

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We analyze the developments of doctoral education in Armenia since 1990 and the management process. Education and training of highly qualified personnel are increasingly seen as a fundamental platform that ensures the development of the state. Reforming the national institute for doctoral studies (aspirantura) is aimed at improving the quality of human resources in science, optimizing research topics in accordance with the priority areas of development of science and technology, increasing publication and innovative activities, bringing national science and research closer to the world level and achieving international recognition. We present a number of defended dissertations in Armenia during the last 30 years, the dynamics and the main trends of the development of the academic degree awarding system. We discuss the possible impact of reforming the system of training and certification of highly qualified personnel on the organization of third–level doctoral education (doctoral schools) and specialized / dissertation councils in Armenia. The results of the SWOT analysis of doctoral education and academic degree awarding processes in Armenia are shown. The article presents the main activities and projects aimed at using the advantages and strong points of the National Academy network in order to improve the quality of doctoral education and training. The paper explores the mechanisms of organizational, methodological and infrastructural support for research and innovation activities of doctoral students and young scientists. There are also suggested approaches to the organization of strong networking between research institutes and foreign universities for training and certification of highly qualified personnel. The authors define the role of ISEC in the management of doctoral studies and the establishment of a competitive third-level education for the sphere of research and development in Armenia.

Keywords: doctoral studies, academic degree, PhD, certification, highly qualified personnel, dissertation, research and development, innovation, networking, management of doctoral school

Procedia PDF Downloads 36

Authors: Rina Lee, Chung-Hun Oh, Eunjin Lee, Jeongyun Kim

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The Photodynamic therapy (PDT) is a treatment that uses a photosensitizer as a drug to damage and kill cancer cells. After injecting the photosensitizer into the bloodstream, the drug is absorbed by cancer cells selectively. Then the area to be treated is exposed to specific wavelengths of light and the photosensitizer produces a form of oxygen that kills nearby cancer cells. PDT is has an advantage to destroy the tumor with minimized side-effects on normal cells. But, PDT is not a completed method for cancer therapy. Because the mechanism of PDT is quite clear yet and the parameters such as intensity of light and dose of photosensitizer are not optimized for different types of cancers. To optimize these parameters, we suggest a novel microfluidic system to automatically control intensity of light exposure with a personal computer (PC). A polydimethylsiloxane (PDMS) microfluidic chip is composed with (1) a cell culture channels layer where cancer cells were trapped to be tested with various dosed photofrin (1μg/ml used for the test) as the photosensitizer and (2) a color dye layer as a neutral density (ND) filter to reduce intensity of light which exposes the cell culture channels filled with cancer cells. Eight different intensity of light (10%, 20%, …, 100%) are generated through various concentrations of blue dye filling the ND filter. As a light source, a light emitting diode (LED) with 635nm wavelength was placed above the developed PDMS microfluidic chip. The total time for light exposure was 30 minutes and HeLa and PC3 cell lines of cancer cells were tested. The cell viability of cells was evaluated with a Live/Dead assay kit (L-3224, Invitrogen, USA). The stronger intensity of light exposed, the lower viability of the cell was observed, and vice versa. Therefore, this system was demonstrated through investigating the PDT against cancer cell to optimize the parameters as critical light intensity and dose of photosensitizer. Our results suggest that the system can be used for optimizing the combinational parameters of light intensity and photosensitizer dose against diverse cancer cell types.

Keywords: photodynamic therapy, photofrin, high throughput screening, hela

Procedia PDF Downloads 359

Authors: Junaid Mahmood Alam

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Revalidating and harmonizing clinical chemistry analytical principles and optimizing methods through quality control programs and assessments is the preeminent means to attain optimal outcome within the clinical laboratory services. Present study reports revalidation of our existing IFCC regularized analytical methods, particularly hepatic and thyroid function tests, by optimization of precision analyses and processing through external and internal quality assessments and regression determination. Parametric components of hepatic (Bilirubin ALT, γGT, ALP), cardiac (LDH, AST, Trop I) and thyroid/pituitary (T3, T4, TSH, FT3, FT4) function tests were used to validate analytical techniques on automated chemistry and immunological analyzers namely Hitachi 912, Cobas 6000 e601, Cobas c501, Cobas e411 with UV kinetic, colorimetric dry chemistry principles and Electro-Chemiluminescence immunoassay (ECLi) techniques. Process of validation and revalidation was completed with evaluating and assessing the precision analyzed Preci-control data of various instruments plotting against each other with regression analyses R2. Results showed that: Revalidation and optimization of respective parameters that were accredited through CAP, CLSI and NEQAPP assessments depicted 99.0% to 99.8% optimization, in addition to the methodology and instruments used for analyses. Regression R2 analysis of BilT was 0.996, whereas that of ALT, ALP, γGT, LDH, AST, Trop I, T3, T4, TSH, FT3, and FT4 exhibited R2 0.998, 0.997, 0.993, 0.967, 0.970, 0.980, 0.976, 0.996, 0.997, 0.997, and R2 0.990, respectively. This confirmed marked harmonization of analytical methods and instrumentations thus revalidating optimized precision standardization as per IFCC recommended guidelines. It is concluded that practices of revalidating and harmonizing the existing or any new services should be followed by all clinical laboratories, especially those associated with tertiary care hospital. This is will ensure deliverance of standardized, proficiency tested, optimized services for prompt and better patient care that will guarantee maximum patients’ confidence.

Keywords: revalidation, standardized, IFCC, CAP, harmonized

Procedia PDF Downloads 230

Authors: Khlifa El Atrash, Gabriel Assaf

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Libya uses a volumetric analysis in designing asphalt mixtures, which can also be upgraded in hot, arid weather. However, in order to be effective, it should include many important aspects which are materials, environment, and method of construction. However, the quality of some roads was below a satisfactory level. This paper examines the factors that contribute to low quality of road performance in Libya. To evaluate these factors, a questionnaire survey and a laboratory comparative study were performed for a few mixes under-represented of temperature and traffic load. In laboratory, rutting test conducted on two different asphalt mixture, these mixes included, an asphalt concrete mix using local aggregate and asphalt binder B(60/70) at the optimum Marshall asphalt content, another mixes designed using Superpave design procedure with the same materials and performance asphalt binder grade PG (70-10). In the survey, the questionnaire was distributed to 55 engineers and specialists in this field. The interview was conducted to a few others, and the factors that were leading to poor performance of asphalt roads were listed as; 1) Owner Experience and technical staff 2) Asphalt characteristics 3) Updating and development of Asphalt Mix Design methods 4) Lack of data collection by authorization Agency 5) Construction and compaction process 6) Mentoring and controlling mixing procedure. Considering and improving these factors will play an important role to improve the pavement performances, longer service life, and lower maintenance costs. This research summarized some recommendations for making asphalt mixtures used in hot, dry areas. Such asphalt mixtures should use asphalt binder which is less affected by pavement temperature change and traffic load. The properties of the mixture, such as durability, deformation, air voids, and performance, largely depend on the type of materials, environment, and mixing method. These properties, in turn, affect the pavement performance.

Keywords: volumetric analysis, pavement performances, hot climate, traffic load, pavement temperature, asphalt mixture, environment, design and construction

Procedia PDF Downloads 238

Authors: Kurias George, Ildefonso Cuesta Romeo, Clara Salueña Pérez, Jordi Sole Olle

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With the growing prevalence of wind energy there is a need, for modeling techniques to evaluate the impact of wind farms on meteorology and oceanography. This study presents an approach that utilizes the WRF (Weather Research and Forecasting )with that include a Wind Farm Parametrization model to simulate the dynamics around Parc Tramuntana project, a offshore wind farm to be located near the Gulf of Roses off the coast of Barcelona, Catalonia. The model incorporates parameterizations for wind turbines enabling a representation of the wind field and how it interacts with the infrastructure of the wind farm. Current results demonstrate that the model effectively captures variations in temeperature, pressure and in both wind speed and direction over time along with their resulting effects on power output from the wind farm. These findings are crucial for optimizing turbine placement and operation thus improving efficiency and sustainability of the wind farm. In addition to focusing on atmospheric interactions, this study delves into the wake effects within the turbines in the farm. A range of meteorological parameters were also considered to offer a comprehensive understanding of the farm's microclimate. The model was tested under different horizontal resolutions and farm layouts to scrutinize the wind farm's effects more closely. These experimental configurations allow for a nuanced understanding of how turbine wakes interact with each other and with the broader atmospheric and oceanic conditions. This modified approach serves as a potent tool for stakeholders in renewable energy, environmental protection, and marine spatial planning. environmental protection and marine spatial planning. It provides a range of information regarding the environmental and socio economic impacts of offshore wind energy projects.

Keywords: weather research and forecasting, wind turbine wake effects, environmental impact, wind farm parametrization, sustainability analysis

Procedia PDF Downloads 38

Authors: Mervat Kassem, Nourhan Fanaki, F. Dabbous, Hamida Abou-Shleib, Y. R. Abdel-Fattah

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With increasing environmental awareness and emphasis on a sustainable society in harmony with the global environment, biosurfactants are gaining prominence and have already taken over for a number of important industrial uses. They are produced by living organisms, for examples Pseudomonas aeruginosa which produces rhamnolipids, Candida (formerly Torulopsis) bombicola, which produces high yields of sophorolipids from vegetable oils and sugars and Bacillus subtilis which produces a lipopeptide called surfactin. The main goal of this work was to optimize biosurfactants production by an environmental Gram positive isolate for large scale production with maximum yield and low cost. After molecular characterization, phylogenetic tree was constructed where it was found to be B. subtilis, which close matches to B. subtilis subsp. subtilis strain CICC 10260. For optimizing its biosurfactants production, sequential statistical design using Plackett-Burman and response surface methodology, was applied where 11 variables were screened. When analyzing the regression coefficients for the 11 variables, pH, glucose, glycerol, yeast extract, ammonium chloride and ammonium nitrate were found to have a positive effect on the biosurfactants production. Ammonium nitrate, pH and glucose were further studied as significant independent variables for Box-Behnken design and their optimal levels were estimated and were found to be 7.328 pH value, 3 g% glucose and 0.21g % ammonium nitrate yielding high biosurfactants concentration that reduced the surface tension of the culture medium from 72 to 18.16 mN/m. Next, kinetics of cell growth and biosurfactants production by the tested B. subtilis isolate, in bioreactor was compared with that of shake flask where the maximum growth and specific growth (µ) in the bioreactor was higher by about 25 and 53%, respectively, than in shake flask experiment, while the biosurfactants production kinetics was almost the same in both shake flask and bioreactor experiments.

Keywords: biosurfactants, B. subtilis, molecular identification, phylogenetic trees, Plackett-Burman design, Box-Behnken design, 16S rRNA

Procedia PDF Downloads 382

Authors: Sahil Kumar, Rajaram Ghadge, Ramesh Bhujade

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Historically, lipid extraction from dried algal biomass remained a focus area of the algal research. It has been realized over the past few years that the lipid-centric approach and conversion technologies that require dry algal biomass have several challenges. Algal culture in cultivation systems contains more than 99% water, with algal concentrations of just a few hundred milligrams per liter ( < 0.05 wt%), which makes harvesting and drying energy intensive. Drying the algal biomass followed by extraction also entails the loss of water and nutrients. In view of these challenges, focus has shifted toward developing processes that will enable oil production from wet algal biomass without drying. Hydrothermal liquefaction (HTL), an emerging technology, is a thermo-chemical conversion process that converts wet biomass to oil and gas using water as a solvent at high temperature and high pressure. HTL processes wet algal slurry containing more than 80% water and significantly reduces the adverse cost impact owing to drying the algal biomass. HTL, being inherently feedstock agnostic, i.e., can convert carbohydrates and proteins also to fuels and recovers water and nutrients. It is most effective with low-lipid (10--30%) algal biomass, and bio-crude yield is two to four times higher than the lipid content in the feedstock. In the early 2010s, research remained focused on increasing the oil yield by optimizing the process conditions of HTL. However, various techno-economic studies showed that simply converting algal biomass to only oil does not make economic sense, particularly in view of low crude oil prices. Making the best use of every component of algae is a key for economic viability of algal to oil process. On investigation of HTL reactions at the molecular level, it has been observed that sequential HTL has the potential to recover value-added products along with biocrude and improve the overall economics of the process. This potential of sequential HTL makes it a most promising technology for converting wet waste to wealth. In this presentation, we will share our experience on the techno-economic and engineering aspects of sequential HTL for conversion of algal biomass to algal bio-oil and co-products.

Keywords: algae, biomass, lipid, protein

Procedia PDF Downloads 183

Authors: Mahima Shrivastava, Soumya Kar, B. Swetha Malika, Lalu Saheb, M. Muthu Kumar, P. V. Ponambala Moorthi

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Natural hazards and manmade destruction causes both economic and societal losses. Generalized pre-mitigation strategies introduced and adopted for prevention of disaster all over the world are capable of augmenting the resiliency and optimizing the life-cycle cost of facilities. In countries like India where varied topographical feature exists requires location specific mitigation measures and strategies to be followed for better enhancement by event-driven and code-driven approaches. Present state of vindication measures followed and adopted, lags dominance in accomplishing the required development. In addition, serious concern and debate over climate change plays a vital role in enhancing the need and requirement for the development of time bound adaptive mitigation measures. For the development of long-term sustainable policies incorporation of future climatic variation is inevitable. This will further assist in assessing the impact brought about by the climate change on life-cycle cost of facilities. This paper develops more definite region specific and time bound pre-mitigation measures, by reviewing the present state of mitigation measures in India and all over the world for improving life-cycle cost of facilities. For the development of region specific adoptive measures, Indian regions were divided based on multiple-calamity prone regions and geo-referencing tools were used to incorporate the effect of climate changes on life-cycle cost assessment. This study puts forward significant effort in establishing sustainable policies and helps decision makers in planning for pre-mitigation measures for different regions. It will further contribute towards evaluating the life cycle cost of facilities by adopting the developed measures.

Keywords: climate change, geo-referencing tools, life-cycle cost, multiple-calamity prone regions, pre-mitigation strategies, sustainable policies

Procedia PDF Downloads 344

Authors: Surya Prakash Gajagouni, Akram Alfantazi, Imad Barsoum

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Austenitic stainless steels are widely recognized for their exceptional corrosion resistance and mechanical properties, rendering them indispensable materials across various industries from construction to biomedical applications. However, in chloride and high temperature atmosphere it to further enhance their surface properties, anodization has emerged as a promising surface treatment technique. Anodization modifies the surface of stainless steels by creating a protective oxide layer, improving corrosion resistance and imparting additional functional characteristics. This paper explores the structural and corrosion characteristics of anodized austenitic stainless steels (AISI 304) using a two-step anodic technique. We utilized a perchloric acid-based electrolyte followed by an ammonium fluoride-based electrolyte. This sequential approach aimed to cultivate deeper and intricately self-ordered nanopore oxide arrays on a substrate made of 304 stainless steel. Electron Microscopic (SEM and TEM) images revealed nanoporous layered structures with increased length and crack development correlating with higher voltage and anodization time. Surface composition and chemical oxidation state of surface-treated SS were determined using X-ray photoelectron spectroscopy (XPS) techniques, revealing a surface layer rich in Ni and suppressed Cr, resulting in a thin film composed of Ni and Fe oxide compared to untreated SS. Electrochemical studies demonstrated enhanced corrosion resistance in a strong alkaline medium compared to untreated SS. Understanding the intricate relationship between the structural features of anodized stainless steels and their corrosion resistance is crucial for optimizing the performance of these materials in diverse applications. This study aims to contribute to the advancement of surface engineering strategies for enhancing the durability and functionality of austenitic stainless steels in aggressive environments.

Keywords: austenitic stainless steel, anodization, nanoporous oxides, marine corrosion

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Authors: Ariba Siddiqui, Amber Khan

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The need for bio-implantable devices in the field of medical sciences has been increasing day by day; however, the charging of these devices is a major issue. Batteries, a very common method of powering the implants, have a limited lifetime and bulky nature. Therefore, as a replacement of batteries, acoustic power transfer (APT) technology is being accepted as the most suitable technique to wirelessly power the medical implants in the present scenario. The basic model of APT consists of piezoelectric transducers that work on the principle of converse piezoelectric effect at the transmitting end and direct piezoelectric effect at the receiving end. This paper provides mechanistic insight into the parameters affecting the design and efficient working of acoustic power transfer systems. The optimum design considerations have been presented that will help to compress the size of the device and augment the intensity of the pressure wave. A COMSOL model of the PZT (Lead Zirconate Titanate) transducer was developed. The model was simulated and analyzed on a frequency spectrum. The simulation results displayed that the efficiency of these devices is strongly dependent on the frequency of operation, and a wrong choice of the operating frequency leads to the high absorption of acoustic field inside the tissue (medium), poor power strength, and heavy transducers, which in effect influence the overall configuration of the acoustic systems. Considering all the tradeoffs, the simulations were performed again by determining an optimum frequency (900 kHz) that resulted in the reduction of the transducer's thickness to 1.96 mm and augmented the power strength with an intensity of 432 W/m². Thus, the results obtained after the second simulation contribute to lesser attenuation, lightweight systems, high power intensity, and also comply with safety limits provided by the U.S Food and Drug Administration (FDA). It was also found that the chosen operating frequency enhances the directivity of the acoustic wave at the receiver side.

Keywords: acoustic power, bio-implantable, COMSOL, Lead Zirconate Titanate, piezoelectric, transducer

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Authors: Moiseenko F. V., Volkov N. M., Zhabina A. S., Stepanova E. O., Kirillov A. V., Myslik A. V., Artemieva E. V., Agranov I. R., Oganesyan A. P., Egorenkov V. V., Abduloeva N. H., Aleksakhina S. Yu., Ivantsov A. O., Kuligina E. S., Imyanitov E. N., Moiseyenko V. M.

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Analysis of ctDNA in patients with NSCLC is an emerging biomarker. Multiple research efforts of quantitative or at least qualitative analysis before and during the first periods of treatment with TKI showed the prognostic value of ctDNA clearance. Still, these important results are not incorporated in clinical standards. We evaluated the role of ctDNA in EGFR-mutated NSCLC receiving first-line TKI. Firstly, we analyzed sequential plasma samples from 30 patients that were collected before intake of the first tablet (at baseline) and at 6, 12, 24, 36, and 48 hours after the “starting point.” EGFR-M+ allele was measured by ddPCR. Afterward, we included sequential qualitative analysis of ctDNA with cobas® EGFR Mutation Test v2 from 99 NSCLC patients before the first dose, after 2 and 4 months of treatment, and on progression. Early response analysis showed the decline of EGFR-M+ level in plasma within the first 48 hours of treatment in 11 subjects. All these patients showed objective tumor response. 10 patients showed either elevation of EGFR-M+ plasma concentration (n = 5) or stable content of circulating EGFR-M+ after the start of the therapy (n = 5); only 3 of these patients achieved an objective response (p = 0.026) when compared to the former group). The rapid decline of plasma EGFR-M+ DNA concentration also predicted for longer PFS (13.7 vs. 11.4 months, p = 0.030). Long-term ctDNA monitoring showed clinically significant heterogeneity of EGFR-mutated NSCLC treated with 1st line TKIs in terms of progression-free and overall survival. Patients without detectable ctDNA at baseline (N = 32) possess the best prognosis on the duration of treatment (PFS: 24.07 [16.8-31.3] and OS: 56.2 [21.8-90.7] months). Those who achieve clearance after two months of TKI (N = 42) have indistinguishably good PFS (19.0 [13.7 – 24.2]). Individuals who retain ctDNA after 2 months (N = 25) have the worst prognosis (PFS: 10.3 [7.0 – 13.5], p = 0.000). 9/25 patients did not develop ctDNA clearance at 4 months with no statistical difference in PFS from those without clearance at 2 months. Prognostic heterogeneity of EGFR-mutated NSCLC should be taken into consideration in planning further clinical trials and optimizing the outcomes of patients.

Keywords: NSCLC, EGFR, targeted therapy, ctDNA, prognosis

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Authors: Taha Benarbia

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The advent of automated and connected vehicles has revolutionized the transportation industry, presenting new opportunities for enhancing the efficiency, safety, and sustainability of our transportation networks. This paper explores the integration of automated and connected vehicles into a smart transportation framework, leveraging the power of deep learning techniques to optimize the overall network performance. The first aspect addressed in this paper is the deployment of automated vehicles (AVs) within the transportation system. AVs offer numerous advantages, such as reduced congestion, improved fuel efficiency, and increased safety through advanced sensing and decisionmaking capabilities. The paper delves into the technical aspects of AVs, including their perception, planning, and control systems, highlighting the role of deep learning algorithms in enabling intelligent and reliable AV operations. Furthermore, the paper investigates the potential of connected vehicles (CVs) in creating a seamless communication network between vehicles, infrastructure, and traffic management systems. By harnessing real-time data exchange, CVs enable proactive traffic management, adaptive signal control, and effective route planning. Deep learning techniques play a pivotal role in extracting meaningful insights from the vast amount of data generated by CVs, empowering transportation authorities to make informed decisions for optimizing network performance. The integration of deep learning with automated and connected vehicles paves the way for advanced transportation network optimization. Deep learning algorithms can analyze complex transportation data, including traffic patterns, demand forecasting, and dynamic congestion scenarios, to optimize routing, reduce travel times, and enhance overall system efficiency. The paper presents case studies and simulations demonstrating the effectiveness of deep learning-based approaches in achieving significant improvements in network performance metrics

Keywords: automated vehicles, connected vehicles, deep learning, smart transportation network

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Authors: Dragan Zivotic, Mirjana Ilic, Aleksandra Perovic, Predrag Gavrilovic

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As with the provision of other services, the service quality perception is one of the key factors that the modern manager must pay attention to. Countries in which the state regulation is in transition also have specific features in providing fitness services. Identification of the dimensions in which the most significant different service quality perception between different types of fitness centers, enables managers to profile the offer according to the wishes and expectations of users. The aim of the paper was the comparison of the quality of services perception in the field of fitness in Serbia between three categories of fitness centers: the privately owned centers, the publicly owned centers, and the Public-private partnership centers. For this research 350 respondents of both genders (174 men and 176 women) were interviewed, aged between 18 and 68 years, being beneficiaries of fitness services for at least 1 year. Administered questionnaire with 100 items provided information about the 15 basic areas in which they expressed the service quality perception in the gym. The core sample was composed of 212 service users in private fitness centers, 69 service users in public fitness centers and 69 service users in the public-private partnership. Sub-samples were equal in representation of women and men, as well as by age and length of use of fitness services. The obtained results were subject of univariate analysis with the Kruskal-Wallis non-parametric analysis of variance. Significant differences between the analyzed sub-samples were not found solely in the areas of rapid response and quality outcomes. In the multivariate model, the results were processed by backward stepwise discriminant analysis that extracted 3 areas that maximize the differences between sub-samples: material and technical basis, secondary facilities and coaches. By applying the classification function 93.87% of private centers services users, 62.32% of public centers services users and 85.51% of the public-private partnership centers users of services were correctly classified (total 86.00%). These results allow optimizing the allocation of the necessary resources in profiling offers of a fitness center in order to optimally adjust it to the user’s needs and expectations.

Keywords: fitness, quality perception, management, public ownership, private ownership, public-private partnership, discriminative analysis

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Authors: Fazl Ullah, Rahmat Ullah

Abstract:

This paper shows a comprehensive learning focused on the optimization of gas production in shale gas reservoirs through hydraulic fracturing. Shale gas has emerged as an important unconventional vigor resource, necessitating innovative techniques to enhance its extraction. The key objective of this study is to examine the influence of fracture parameters on reservoir productivity and formulate strategies for production optimization. A sophisticated model integrating gas flow dynamics and real stress considerations is developed for hydraulic fracturing in multi-stage shale gas reservoirs. This model encompasses distinct zones: a single-porosity medium region, a dual-porosity average region, and a hydraulic fracture region. The apparent permeability of the matrix and fracture system is modeled using principles like effective stress mechanics, porous elastic medium theory, fractal dimension evolution, and fluid transport apparatuses. The developed model is then validated using field data from the Barnett and Marcellus formations, enhancing its reliability and accuracy. By solving the partial differential equation by means of COMSOL software, the research yields valuable insights into optimal fracture parameters. The findings reveal the influence of fracture length, diversion capacity, and width on gas production. For reservoirs with higher permeability, extending hydraulic fracture lengths proves beneficial, while complex fracture geometries offer potential for low-permeability reservoirs. Overall, this study contributes to a deeper understanding of hydraulic cracking dynamics in shale gas reservoirs and provides essential guidance for optimizing gas production. The research findings are instrumental for energy industry professionals, researchers, and policymakers alike, shaping the future of sustainable energy extraction from unconventional resources.

Keywords: fluid-solid coupling, apparent permeability, shale gas reservoir, fracture property, numerical simulation

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Authors: Nwachukwu Ifeanyi

Abstract:

Wind energy is a vital component of the global renewable energy portfolio, with wind turbines serving as the primary means of harnessing this abundant resource. However, the efficiency and stability of wind turbines remain critical challenges in maximizing energy output and ensuring long-term operational viability. This study proposes a comprehensive approach utilizing computational aerodynamics and aeromechanics to optimize wind turbine performance across multiple objectives. The proposed research aims to integrate advanced computational fluid dynamics (CFD) simulations with structural analysis techniques to enhance the aerodynamic efficiency and mechanical stability of wind turbine blades. By leveraging multi-objective optimization algorithms, the study seeks to simultaneously optimize aerodynamic performance metrics such as lift-to-drag ratio and power coefficient while ensuring structural integrity and minimizing fatigue loads on the turbine components. Furthermore, the investigation will explore the influence of various design parameters, including blade geometry, airfoil profiles, and turbine operating conditions, on the overall performance and stability of wind turbines. Through detailed parametric studies and sensitivity analyses, valuable insights into the complex interplay between aerodynamics and structural dynamics will be gained, facilitating the development of next-generation wind turbine designs. Ultimately, this research endeavours to contribute to the advancement of sustainable energy technologies by providing innovative solutions to enhance the efficiency, reliability, and economic viability of wind power generation systems. The findings have the potential to inform the design and optimization of wind turbines, leading to increased energy output, reduced maintenance costs, and greater environmental benefits in the transition towards a cleaner and more sustainable energy future.

Keywords: computation, robotics, mathematics, simulation

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Authors: Ruiyi Zhang, Wanglin Yan

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Strict land-use plan is issued based on city planning act for controlling urbanization and conserving semi-natural landscape. And the agrarian land resource in the suburbs has indispensable socio-economic value and contributes to the sustainability of the regional environment. However, the agrarian hinterland of metropolitan is witnessing severe farmland conversion and abandonment, while the contribution of land-use planning to farmland conservation remains unclear in those areas. Hypothetically, current land-use plan contributes to farmland loss. So, this research investigated the relationship between farmland loss and land-use planning at municipality level to provide base data for zoning in the metropolitan suburbs, and help to develop a sustainable land-use plan that will conserve the agrarian hinterland. As data and methods, 1) Farmland data of Census of Agriculture and Forestry for 2005 to 2015 and population data of 2015 and 2018 were used to investigate spatial distribution feathers of farmland loss in Tokyo Metropolitan District (TMD) for two periods: 2005-2010;2010-2015. 2) And the samples were divided by four urbanization facts. 3) DID data and zoning data for 2006 to 2018 were used to specify urbanization level of zones for describing land-use plan. 4) Then we conducted multiple regression between farmland loss, both abandonment and conversion amounts, and the described land-use plan in each of the urbanization scenario and in each period. As the results, the study reveals land-use plan has unignorable relation with farmland loss in the metropolitan suburbs at ward-city-town-village level. 1) The urban promotion areas planned larger than necessity and unregulated urbanization promote both farmland conversion and abandonment, and the effect weakens from inner suburbs to outer suburbs. 2) And the effect of land-use plan on farmland abandonment is more obvious than that on farmland conversion. The study advocates that, optimizing land-use plan will hopefully help the farmland conservation in metropolitan suburbs, which contributes to sustainable regional policy making.

Keywords: Agrarian land resource, land-use planning, urbanization level, multiple regression

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Authors: Annika Stechemesser, Rachel Pounds, Emma Lucas, Chris Dawson, Julia Lipecki, Pavle Vrljicak, Jan Brosens, Sean Kehoe, Jason Yap, Lawrence Young, Sascha Ott

Abstract:

Advances in technology make it now possible to retrieve the genetic information of thousands of single cancerous cells. One of the key challenges in single cell analysis of cancerous tissue is to determine the number of different cell types and their characteristic genes within the sample to better understand the tumors and their reaction to different treatments. For this analysis to be possible, it is crucial to filter out background noise as it can severely blur the downstream analysis and give misleading results. In-depth analysis of the state-of-the-art filtering methods for single cell data showed that they do, in some cases, not separate noisy and normal cells sufficiently. We introduced an algorithm that filters and clusters single cell data simultaneously without relying on certain genes or thresholds chosen by eye. It detects communities in a Shared Nearest Neighbor similarity network, which captures the similarities and dissimilarities of the cells by optimizing the modularity and then identifies and removes vertices with a weak clustering belonging. This strategy is based on the fact that noisy data instances are very likely to be similar to true cell types but do not match any of these wells. Once the clustering is complete, we apply a set of evaluation metrics on the cluster level and accept or reject clusters based on the outcome. The performance of our algorithm was tested on three datasets and led to convincing results. We were able to replicate the results on a Peripheral Blood Mononuclear Cells dataset. Furthermore, we applied the algorithm to two samples of ovarian cancer from the same patient before and after chemotherapy. Comparing the standard approach to our algorithm, we found a hidden cell type in the ovarian postchemotherapy data with interesting marker genes that are potentially relevant for medical research.

Keywords: cancer research, graph theory, machine learning, single cell analysis

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Authors: Dheyaa W. Abbood, Rafa H. AL-Suhaili, May S. Saleh

Abstract:

A model using the artificial neural networks and genetic algorithm technique is developed for obtaining optimum dimensions of the foundation length and protections of small hydraulic structures. The procedure involves optimizing an objective function comprising a weighted summation of the state variables. The decision variables considered in the optimization are the upstream and downstream cutoffs length sand their angles of inclination, the foundation length, and the length of the downstream soil protection. These were obtained for a given maximum difference in head, depth of impervious layer and degree of anisotropy.The optimization carried out subjected to constraints that ensure a safe structure against the uplift pressure force and sufficient protection length at the downstream side of the structure to overcome an excessive exit gradient. The Geo-studios oft ware, was used to analyze 1200 different cases. For each case the length of protection and volume of structure required to satisfy the safety factors mentioned previously were estimated. An ANN model was developed and verified using these cases input-output sets as its data base. A MatLAB code was written to perform a genetic algorithm optimization modeling coupled with this ANN model using a formulated optimization model. A sensitivity analysis was done for selecting the cross-over probability, the mutation probability and level ,the number of population, the position of the crossover and the weights distribution for all the terms of the objective function. Results indicate that the most factor that affects the optimum solution is the number of population required. The minimum value that gives stable global optimum solution of this parameters is (30000) while other variables have little effect on the optimum solution.

Keywords: inclined cutoff, optimization, genetic algorithm, artificial neural networks, geo-studio, uplift pressure, exit gradient, factor of safety

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Authors: Felipe Henao, Yeny Rodriguez, Juan P. Viteri, Isaac Dyner

Abstract:

Colombia is rich in natural resources and greatly focuses on the exploitation of water for hydroelectricity purposes. Alternative cleaner energy sources, such as solar and wind power, have been largely neglected despite: a) its abundance, b) the complementarities between hydro, solar and wind power, and c) the cost competitiveness of renewable technologies. The current limited mix of energy sources creates considerable weaknesses for the system, particularly when facing extreme dry weather conditions, such as El Niño event. In the past, El Niño have exposed the truly consequences of a system heavily dependent on hydropower, i.e. loss of power supply, high energy production costs, and loss of overall competitiveness for the country. Nonetheless, it is expected that the participation of hydroelectricity will increase in the near future. In this context, this paper proposes a stochastic lineal programming model to optimize the insertion of renewable energy systems (RES) into the Colombian electricity sector. The model considers cost-based generation competition between traditional energy technologies and alternative RES. This work evaluates the financial, environmental, and technical implications of different combinations of technologies. Various scenarios regarding the future evolution of costs of the technologies are considered to conduct sensitivity analysis of the solutions – to assess the extent of the participation of the RES in the Colombian power sector. Optimization results indicate that, even in the worst case scenario, where costs remain constant, the Colombian power sector should diversify its portfolio of technologies and invest strongly in solar and wind power technologies. The diversification through RES will contribute to make the system less vulnerable to extreme weather conditions, reduce the overall system costs, cut CO2 emissions, and decrease the chances of having national blackout events in the future. In contrast, the business as usual scenario indicates that the system will turn more costly and less reliable.

Keywords: energy policy and planning, stochastic programming, sustainable development, water management

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Authors: Muhammad Awais Kiani, Maryam Kiani

Abstract:

This abstract explores the confluence of these two domains and highlights the key factors driving success in sales marketing for electronics. The abstract begins by digging into the ever-evolving landscape of consumer electronics, emphasizing how technological advancements and the growth of smart devices have revolutionized the way people interact with electronics. This paradigm shift has created tremendous opportunities for sales and marketing professionals to engage with consumers on various platforms and channels. Next, the abstract discusses the pivotal role of effective sales marketing strategies in the electronics industry. It highlights the importance of understanding consumer behavior, market trends, and competitive landscapes and how this knowledge enables businesses to tailor their marketing efforts to specific target audiences. Furthermore, the abstract explores the significance of leveraging digital marketing techniques, such as social media advertising, search engine optimization, and influencer partnerships, to establish brand identity and drive sales in the electronics market. It emphasizes the power of storytelling and creating captivating content to engage with tech-savvy consumers. Additionally, the abstract emphasizes the role of customer relationship management (CRM) systems and data analytics in optimizing sales marketing efforts. It highlights the importance of leveraging customer insights and analyzing data to personalize marketing campaigns, enhance customer experience, and ultimately drive sales growth. Lastly, the abstract concludes by underlining the importance of adapting to the ever-changing landscape of the electronics industry. It encourages businesses to embrace innovation, stay informed about emerging technologies, and continuously evolve their sales marketing strategies to meet the evolving needs and expectations of consumers. Overall, this abstract sheds light on the captivating realm of sales marketing in the electronics industry, emphasizing the need for creativity, adaptability, and a deep understanding of consumers to succeed in this rapidly evolving market.

Keywords: marketing industry, electronics, sales impact, e-commerce

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